FACE RECOGNITION Technique using Multi-channel Gabor Filter and Center-symmetry Local Binary Pattern

摘要

The present invention relates to an improved multi-channel Gabor filter-based human face recognition method. If an input is a face image of N persons (N is a natural number of two or more) and an output is an image of a cascaded particle histogram feature vector representation of statistics, the present invention includes: a first step of obtaining a feature image (,); a second step of dividing a plurality of overlapping sub images in the same manner; and a third step of generating a histogram of all the sub images to extract a cascade histogram feature vector sequence. By combining a Gabor filter and center-symmetry local binary patterns (CS-LBP), it is possible to extract noise-robust feature points and reduce the dimensionality of extracted facial feature points.